General rights
Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.
Users may download and print one copy of any publication from the public portal for the purpose of private study or research.
You may not further distribute the material or use it for any profit-making activity or commercial gain
You may freely distribute the URL identifying the publication in the public portal
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Downloaded from orbit.dtu.dk on: Mar 24, 2022
Kan vi få et bedre miljø med smartere kloakker?
Vezzaro, Luca
Publication date:
2018
Document Version
Også kaldet Forlagets PDF Link back to DTU Orbit
Citation (APA):
Vezzaro, L. (Forfatter). (2018). Kan vi få et bedre miljø med smartere kloakker?. Lyd og/eller billed produktion (digital), DTU Miljø, Danmarks Tekniske Universtitet.
Kan vi få et bedre miljø med smartere kloakker?
Lektor Luca Vezzaro Forskning Døgn
Slagelse, d. 26. april 2018
Lidt om mig
• Født i Padova, tæt på Venedig
• Uddannet som miljøingeniør
• Kom til Danmark som udvekslingsstudent i 2005
• PhD om modellering af miljøfremmede stoffer i regnvand (2011)
• Jeg arbejder på DTU Miljø, hvor jeg forsker i styring og modellering af afløbssystemer
• Deltid ansat hos Krüger Veolia A/S (jeg tager forskning ud i ”den virkelige verden”)
Why do we have sewers?
Why do we have sewers?
Before 1800 (Western Cities)
Ferriman, A. 2007. “BMJ Readers Choose the ‘Sanitary Revolution’ as Greatest Medical
Our cities when sun is shining…
Wastewater Treatment Plant
From www.aldrigsur.dk/ved-stranden www. http://natmus.dk/museerne/brede-vaerk/
Wastewater Treatment Plant
…but sometimes it rains…
WWTP
…and it rains more…
Combined Sewer Overflows (CSO)
Photo by Linea Sofie Skov
WWTP
bypass
WWTP
…and it rains more…
Combined Sewer Overflows (CSO)
Photo by Linea Sofie Skov
WWTP bypass Pollutant contribution from
point discharges in DK (2015)
Source: Miljø- og Fødevareministeriet Styrelsen for Vand- og Naturforvaltning (2017) . Punktkilder 2015
35% 31%
21%
WWTP
…and it rains more…
Combined Sewer Overflows (CSO)
Photo by Linea Sofie Skov
WWTP bypass Pollutant contribution from
point discharges in DK (2015)
Source: Miljø- og Fødevareministeriet Styrelsen for Vand- og Naturforvaltning (2017) . Punktkilder 2015
Once upon a time in Denmark
The good old operator
The good old operator
From lego.wikia.com
I need to optimize the performance of my system
(without building a lot of new expensive things)
Smart people from university, please
help me!
Once upon a time in Denmark
Many projects
Storm- and Wastewater Informatics (SWI) Klimaspring
Prepared AMOK
Water Smart Cities Industrial PhDs
Industrial postdocs Many MSc theses
Universities + research institutions + water utilities + consultants
2007-now … a range of activities
WWTP
One option to avoid overflow…
Detention basis
WWTP
Real Time Control of drainage network
Rain is not uniform we can optimize the storage across the system less overflow WWTP doesn’t like high flows we can regulate the inlet flow to the WWTP less bypass
WWTP
Real Time Control of drainage network
Rain is not uniform we can optimize the storage across the system less overflow WWTP doesn’t like high flows we can regulate the inlet flow to the WWTP less bypass
WWTP
Model Predictive Control
We can forecast rainfall where and how much is going to rain even less CSO We can forecast WWTP status how much water the WWTP can treat even less bypass
Weather models Radar
WWTP models
WWTP
Model Predictive Control
We can forecast rainfall where and how much is going to rain even less CSO We can forecast WWTP status how much water the WWTP can treat even less bypass
Weather models Radar
WWTP models
How much water will there be in next 2 hours?
The SWI concept
Measurements Models Forecasts Uncertainty
The happy operator
The fellowship of SWI – the long journey
Control Strategy
Model
now
Model Model
Rainfall measurements
Short-term rainfall forecasts Continuously updated
hydrodynamic models
Stochastic rainfall-runoff forecast WWTP forecast models
MPC strategy addressing uncertainty
Measurements Models Forecasts Uncertainty
The happy operator
Control Strategy
Model
now
Model Model
Measurements Models Forecasts Uncertainty
The happy operator Rainfall measurements
Short-term rainfall forecasts Continuously updated
hydrodynamic models Stochastic rainfall-runoff forecast
WWTP forecast models MPC strategy addressing uncertainty
The fellowship of SWI – the long journey
Rainfall input
Where is it raining?
And how much?
Rainfall is not easy to measure
Rain gauge
Slagelse Pumpestation (5485) Slagelse centralrenseanlæg (5490)
Radar
Rainfall input
Where is it raining?
And how much?
Rainfall is not easy to measure
Volume Spatial distribution
Rain gauges √ X
Radar X √
Flow measurements ? ?
Slide courtesy of SørenThorndahl
But you can combine them
Søren Thorndahl – Department of Civil Engineering Aalborg University 26
The new AAU Nowcaster
The spatial resolution is 16 times higher than before (500x500m vs 2000x2000m)
Before After
Søren Thorndahl – Department of Civil Engineering Aalborg University
Demonstration af online nowcaster (WP-3)
Slide courtesy of Jesper EllerbækNielsen
Radar resolution
• Which one is the good one for the urban scale?
• Radar can are only useful to predict up to 2 hrs in the future
• What about longer horizons?
• Numerical Weather Prediction (NWP) models
Thorndahl, S., Einfalt, T., Willems, P., Nielsen, J. E., ten Veldhuis, M.-C., Arnbjerg-Nielsen, K., … Molnar, P. (2017). Weather radar rainfall data in urban hydrology. Hydrology and Earth System Sciences, 21(3), 1359–
Søren Thorndahl – Department of Civil Engineering Aalborg University
Flow forecast results - Event 6: 21 – 24 January 2012
29
21-01-2012 00:000 22-01-2012 00:00 23-01-2012 00:00 24-01-2012 00:00
2 4 6 8 10 12
UTC
Flow (m3 /s)
Measured Radar observed Radar nowcast 1 h Radar nowcast 2 h
21-01-2012 00:000 22-01-2012 00:00 23-01-2012 00:00 24-01-2012 00:00
2 4 6 8 10 12
UTC
Flow (m3 /s)
Measured
Weather model 6 h Weather model 12 h Weather model 24 h
Mean rain gauge accum.: 8.6 mm Mean obs. radar accum.: 7.3 mm
Now 2 hr
Goodness of
forecast Radar
NWP
Hvordan er vejret i dag?
Slagelse - 19/04
Slagelse - 20/04
Slagelse - 21/04
Slagelse - 22/04
Slagelse - 23/04
Slagelse - 24/04
Slagelse - 25/04
How weather forecasts are made?
The DMI-HIRLAM-S05 model
Ensemble
members STRACO KF/RK STRACO
Stoc. Phys. Stoc. Phys. Pert. Roughn.
Ini. cond. 1 1 6 11 16 21
Ini. cond. 2 2 7 12 17 22
Ini. cond. 3 3 8 13 18 23
Ini. cond. 4 4 9 14 19 24
Ini. cond. 5 5 10 15 20 25
● Horizontal resolution = 0.05° (5.5 km)
● Time Step = 1h
● Forecast length = 54h
● Forecast frequency = 4 times per day
● Members = 25
5 ≠ model structures
5 ≠ in itia l co nd itio n s
Slide courtesy of Dr. Vianney Courdant
Context vs. Model Uncertainty what do we ask to the model?
Meteorological perspective
Weather behavior, pattern, feature
Urban hydrology perspective
Local value with high resolution
The big picture The pixel
Slide courtesy of Dr. Vianney Courdant
Context vs. Model Uncertainty what do we ask to the model?
Meteorological perspective Urban hydrology perspective
Slide courtesy of Vianney Courdant
These weather forecast are crap These weather
forecast are great!
DMI model prediction (winter)
Slide courtesy of Dr. Vianney Courdant
DMI model prediction (summer)
Slide courtesy of Dr. Vianney Courdant
Control Strategy
Model
now
Model Model
Measurements Models Forecasts Uncertainty
The happy operator Rainfall measurements
Short-term rainfall forecasts Continuously updated
hydrodynamic models Stochastic rainfall-runoff forecast
WWTP forecast models MPC strategy addressing uncertainty
The fellowship of SWI – the long journey
WWTP
Model Predictive Control with uncertainty
Rainfall forecasts are uncertain we need to make decisions considering also this uncertainty
Uncertainty bounds
Stochastic runoff forecasts
Observations
1000 simulations
V [m3]
time Rainfall-
runoff model
Stochastic runoff forecasts
Observations
1000 simulations
V [m3]
time
90% probability Rainfall-
runoff model
Control Strategy
Model
now
Model Model
Measurements Models Forecasts Uncertainty
The happy operator Rainfall measurements
Short-term rainfall forecasts Continuously updated
hydrodynamic models Stochastic rainfall-runoff forecast
WWTP forecast models MPC strategy addressing uncertainty
The fellowship of SWI – the long journey
Controlling the WWTP based on energy prices
the Blue Kolding example
Slidecourtesy of Rasmus FogtmannHalvgaard
Integrated Control
€ kgN
MPC model
€
Controlling the WWTP based on energy prices – moving
upstream
Slidecourtesy of Rasmus Fogtmann Halvgaard and Julie Evald Bjerg
P1
P2
Reduce CSO
Controlling the WWTP based on energy prices – moving
upstream
Slidecourtesy of Julie Evald Bjerg and Vianney Courdant
P1
P2
Optimize WWTP Operations
Controlling the WWTP based on energy prices – moving
upstream
Slidecourtesy of Julie Evald Bjerg and Vianney Courdant
P1
P2
Optimize WWTP Operations
Numerical Weather Prediction models are used to switch between the two controls
Control Strategy
Model
now
Model Model
Measurements Models Forecasts Uncertainty
The happy operator Rainfall measurements
Short-term rainfall forecasts Continuously updated
hydrodynamic models Stochastic rainfall-runoff forecast
WWTP forecast models MPC strategy addressing uncertainty
The fellowship of SWI – the long journey
Why uncertainty matters
Didactical example
Detention
basins Treatment
plant
West Town East Town
Real Time Control
Objective:Maximize storage
West Town East Town
Model forecast (without uncertainty)
“Traditional” MPC
Objective:Maximize future storage
√ ?
Rainfall evolution is uncertainRisk-based Model Predictive Control
Target
Target
West Town East Town
If we do not consider uncertainty If we consider uncertainty
Risk of overflow
Objective:
Minimize CSO risk
Risk-based Model Predictive Control
The Dynamic Overflow Risk Analysis (DORA)
Dynamic Overflow Risk Assessment (DORA) Radar-based runoff
prediction
Uncertainty of forecasts
On-line data
Optimal set-points
Vezzaro, L., & Grum, M. (2014). J. Hydrology, 515, doi:10 1016/j jhydrol 2014 05 019
The Lynetten catchment
Central Copenhagen, Denmark
West Amager (13,500 m3)
East Amager (44,400 m3) Kloevermarken
(27,500 m3)
Lynetten (WWTP) St. Anne
(8,000 m3)
Strandvaenget (basin) (60 m3)
Lersoeledning
(27,000 m3) Strandvaenget (pump)
(no storage)
Sensitivity of overflow recipient
CSO ”price”
€
€
€
€€
€
€
€ €
Control Strategy
Model
now
Model Model
Measurements Models Forecasts Uncertainty
The happy operator Rainfall measurements
Short-term rainfall forecasts Continuously updated
hydrodynamic models Stochastic rainfall-runoff forecast
WWTP forecast models MPC strategy addressing uncertainty
What’s next?
The fellowship of SWI – the long journey
WWTP
Water Quality-based control
Pollutant concentrations are not uniform we can control the system based on Water Quality (instead of water quantity)
WWTP
Water Quality-based control
Pollutant concentrations are not uniform we can control the system based on Water Quality (instead of water quantity)
The natural waters have not all the same status we can avoid CSO where it makes bigger damage
On-line water quality data
Alferes et al. (2014), Advanced monitoring of wastewater quality: data collection and data
quality assurance, Proceedings of 13th ICUD2014
I have
thousand other things to do!
NH4
The big challenge of online water quality measurements
Photo by Linea Sofie SkovPhoto by Ravi Kumar Chhetri
Sensor
Maintenance
Multivariate DQC Software Sensors
…
WHAT????
Which language is he/she
talking?
The Ålebækken ”playground”
Slide credits: Linea S. Skov
How much can we trust sensors?
Slide credits: Linea S. Skov
Do we need fancy sensors at all?
Slide credits: Camilla Høj &
Karin L. Drenck
The importance of involving the final users
From lego.wikia.com
Dear smart people from university, what wonderful tool did you
prepare for me?
With a genetic algorithm which minimizes risks you
will….
We have an Extended Kalman Filter to assimilate data and…
If you use a stochastic differential equation…
Can you please make a if-then scheme of you
advanced control?
??????
Thanks, but my system works fine as it is
The importance of involving the final users
From lego.wikia.com
Making a smart tool is not enough – you need somebody ready to use it
Collaboration between universities and final user is essential
Conclusions
towards a better environment with smarter sewer systems
We can have a better environment if we use our sewers in a smarter way
We have now new tools for on-line model-based operation of integrated urban wastewater systems (more than 10 years of research/development)
Measurements Models Forecasts Uncertainty
The happy operator
Thank you for listening!
An overflow expert
luve@env.dtu.dk
